<!DOCTYPE html>
<html lang="en">
<head>
    <meta http-equiv="content-type" content="text/html;charset=utf-8"/>
    <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
    <meta name="description" content="This experiment generates MNIST images using multi-layer perceptron."/>

    <meta name="twitter:card" content="summary"/>
    <meta name="twitter:image:src" content="https://avatars1.githubusercontent.com/u/64068543?s=400&amp;v=4"/>
    <meta name="twitter:title" content="Generative Adversarial Networks experiment with MNIST"/>
    <meta name="twitter:description" content="This experiment generates MNIST images using multi-layer perceptron."/>
    <meta name="twitter:site" content="@labmlai"/>
    <meta name="twitter:creator" content="@labmlai"/>

    <meta property="og:url" content="https://nn.labml.ai/gan/original/experiment.html"/>
    <meta property="og:title" content="Generative Adversarial Networks experiment with MNIST"/>
    <meta property="og:image" content="https://avatars1.githubusercontent.com/u/64068543?s=400&amp;v=4"/>
    <meta property="og:site_name" content="Generative Adversarial Networks experiment with MNIST"/>
    <meta property="og:type" content="object"/>
    <meta property="og:title" content="Generative Adversarial Networks experiment with MNIST"/>
    <meta property="og:description" content="This experiment generates MNIST images using multi-layer perceptron."/>

    <title>Generative Adversarial Networks experiment with MNIST</title>
    <link rel="shortcut icon" href="/icon.png"/>
    <link rel="stylesheet" href="../../pylit.css?v=1">
    <link rel="canonical" href="https://nn.labml.ai/gan/original/experiment.html"/>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.13.18/dist/katex.min.css" integrity="sha384-zTROYFVGOfTw7JV7KUu8udsvW2fx4lWOsCEDqhBreBwlHI4ioVRtmIvEThzJHGET" crossorigin="anonymous">

    <!-- Global site tag (gtag.js) - Google Analytics -->
    <script async src="https://www.googletagmanager.com/gtag/js?id=G-4V3HC8HBLH"></script>
    <script>
        window.dataLayer = window.dataLayer || [];

        function gtag() {
            dataLayer.push(arguments);
        }

        gtag('js', new Date());

        gtag('config', 'G-4V3HC8HBLH');
    </script>
</head>
<body>
<div id='container'>
    <div id="background"></div>
    <div class='section'>
        <div class='docs'>
            <p>
                <a class="parent" href="/">home</a>
                <a class="parent" href="../index.html">gan</a>
                <a class="parent" href="index.html">original</a>
            </p>
            <p>
                <a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations" target="_blank">
                    <img alt="Github"
                         src="https://img.shields.io/github/stars/labmlai/annotated_deep_learning_paper_implementations?style=social"
                         style="max-width:100%;"/></a>
                <a href="https://twitter.com/labmlai" rel="nofollow" target="_blank">
                    <img alt="Twitter"
                         src="https://img.shields.io/twitter/follow/labmlai?style=social"
                         style="max-width:100%;"/></a>
            </p>
            <p>
                <a href="https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/gan/original/experiment.py" target="_blank">
                    View code on Github</a>
            </p>
        </div>
    </div>
    <div class='section' id='section-0'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-0'>#</a>
            </div>
            <h1>Generative Adversarial Networks experiment with MNIST</h1>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">10</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span>
<span class="lineno">11</span>
<span class="lineno">12</span><span class="kn">from</span> <span class="nn">torchvision</span> <span class="kn">import</span> <span class="n">transforms</span>
<span class="lineno">13</span>
<span class="lineno">14</span><span class="kn">import</span> <span class="nn">torch</span>
<span class="lineno">15</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="lineno">16</span><span class="kn">import</span> <span class="nn">torch.utils.data</span>
<span class="lineno">17</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">tracker</span><span class="p">,</span> <span class="n">monit</span><span class="p">,</span> <span class="n">experiment</span>
<span class="lineno">18</span><span class="kn">from</span> <span class="nn">labml.configs</span> <span class="kn">import</span> <span class="n">option</span><span class="p">,</span> <span class="n">calculate</span>
<span class="lineno">19</span><span class="kn">from</span> <span class="nn">labml_nn.gan.original</span> <span class="kn">import</span> <span class="n">DiscriminatorLogitsLoss</span><span class="p">,</span> <span class="n">GeneratorLogitsLoss</span>
<span class="lineno">20</span><span class="kn">from</span> <span class="nn">labml_nn.helpers.datasets</span> <span class="kn">import</span> <span class="n">MNISTConfigs</span>
<span class="lineno">21</span><span class="kn">from</span> <span class="nn">labml_nn.helpers.device</span> <span class="kn">import</span> <span class="n">DeviceConfigs</span>
<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml_nn.helpers.optimizer</span> <span class="kn">import</span> <span class="n">OptimizerConfigs</span>
<span class="lineno">23</span><span class="kn">from</span> <span class="nn">labml_nn.helpers.trainer</span> <span class="kn">import</span> <span class="n">TrainValidConfigs</span><span class="p">,</span> <span class="n">BatchIndex</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-1'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-1'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">26</span><span class="k">def</span> <span class="nf">weights_init</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
<span class="lineno">27</span>    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
<span class="lineno">28</span>    <span class="k">if</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Linear&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
<span class="lineno">29</span>        <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
<span class="lineno">30</span>    <span class="k">elif</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;BatchNorm&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
<span class="lineno">31</span>        <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
<span class="lineno">32</span>        <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-2'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-2'>#</a>
            </div>
            <h3>Simple MLP Generator</h3>
<p>This has three linear layers of increasing size with <code  class="highlight"><span></span><span class="n">LeakyReLU</span></code>
 activations. The final layer has a <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal">t</span><span class="mord mathnormal">anh</span></span></span></span></span> activation.</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">35</span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-3'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-3'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">43</span>    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="lineno">44</span>        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="lineno">45</span>        <span class="n">layer_sizes</span> <span class="o">=</span> <span class="p">[</span><span class="mi">256</span><span class="p">,</span> <span class="mi">512</span><span class="p">,</span> <span class="mi">1024</span><span class="p">]</span>
<span class="lineno">46</span>        <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
<span class="lineno">47</span>        <span class="n">d_prev</span> <span class="o">=</span> <span class="mi">100</span>
<span class="lineno">48</span>        <span class="k">for</span> <span class="n">size</span> <span class="ow">in</span> <span class="n">layer_sizes</span><span class="p">:</span>
<span class="lineno">49</span>            <span class="n">layers</span> <span class="o">=</span> <span class="n">layers</span> <span class="o">+</span> <span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="n">size</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">LeakyReLU</span><span class="p">(</span><span class="mf">0.2</span><span class="p">)]</span>
<span class="lineno">50</span>            <span class="n">d_prev</span> <span class="o">=</span> <span class="n">size</span>
<span class="lineno">51</span>
<span class="lineno">52</span>        <span class="bp">self</span><span class="o">.</span><span class="n">layers</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="mi">28</span> <span class="o">*</span> <span class="mi">28</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span>
<span class="lineno">53</span>
<span class="lineno">54</span>        <span class="bp">self</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-4'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-4'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">56</span>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="lineno">57</span>        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">28</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-5'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-5'>#</a>
            </div>
            <h3>Simple MLP Discriminator</h3>
<p>This has three linear layers of decreasing size with <code  class="highlight"><span></span><span class="n">LeakyReLU</span></code>
 activations. The final layer has a single output that gives the logit of whether input is real or fake. You can get the probability by calculating the sigmoid of it.</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">60</span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-6'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-6'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">69</span>    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="lineno">70</span>        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="lineno">71</span>        <span class="n">layer_sizes</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1024</span><span class="p">,</span> <span class="mi">512</span><span class="p">,</span> <span class="mi">256</span><span class="p">]</span>
<span class="lineno">72</span>        <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
<span class="lineno">73</span>        <span class="n">d_prev</span> <span class="o">=</span> <span class="mi">28</span> <span class="o">*</span> <span class="mi">28</span>
<span class="lineno">74</span>        <span class="k">for</span> <span class="n">size</span> <span class="ow">in</span> <span class="n">layer_sizes</span><span class="p">:</span>
<span class="lineno">75</span>            <span class="n">layers</span> <span class="o">=</span> <span class="n">layers</span> <span class="o">+</span> <span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="n">size</span><span class="p">),</span> <span class="n">nn</span><span class="o">.</span><span class="n">LeakyReLU</span><span class="p">(</span><span class="mf">0.2</span><span class="p">)]</span>
<span class="lineno">76</span>            <span class="n">d_prev</span> <span class="o">=</span> <span class="n">size</span>
<span class="lineno">77</span>
<span class="lineno">78</span>        <span class="bp">self</span><span class="o">.</span><span class="n">layers</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">d_prev</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="lineno">79</span>        <span class="bp">self</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-7'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-7'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">81</span>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="lineno">82</span>        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">layers</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="o">-</span><span class="mi">1</span><span class="p">))</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-8'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-8'>#</a>
            </div>
            <h2>Configurations</h2>
<p>This extends MNIST configurations to get the data loaders and Training and validation loop configurations to simplify our implementation.</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">85</span><span class="k">class</span> <span class="nc">Configs</span><span class="p">(</span><span class="n">MNISTConfigs</span><span class="p">,</span> <span class="n">TrainValidConfigs</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-9'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-9'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">93</span>    <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">DeviceConfigs</span><span class="p">()</span>
<span class="lineno">94</span>    <span class="n">dataset_transforms</span> <span class="o">=</span> <span class="s1">&#39;mnist_gan_transforms&#39;</span>
<span class="lineno">95</span>    <span class="n">epochs</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span>
<span class="lineno">96</span>
<span class="lineno">97</span>    <span class="n">is_save_models</span> <span class="o">=</span> <span class="kc">True</span>
<span class="lineno">98</span>    <span class="n">discriminator</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span> <span class="o">=</span> <span class="s1">&#39;mlp&#39;</span>
<span class="lineno">99</span>    <span class="n">generator</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span> <span class="o">=</span> <span class="s1">&#39;mlp&#39;</span>
<span class="lineno">100</span>    <span class="n">generator_optimizer</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span>
<span class="lineno">101</span>    <span class="n">discriminator_optimizer</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span>
<span class="lineno">102</span>    <span class="n">generator_loss</span><span class="p">:</span> <span class="n">GeneratorLogitsLoss</span> <span class="o">=</span> <span class="s1">&#39;original&#39;</span>
<span class="lineno">103</span>    <span class="n">discriminator_loss</span><span class="p">:</span> <span class="n">DiscriminatorLogitsLoss</span> <span class="o">=</span> <span class="s1">&#39;original&#39;</span>
<span class="lineno">104</span>    <span class="n">label_smoothing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span>
<span class="lineno">105</span>    <span class="n">discriminator_k</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-10'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-10'>#</a>
            </div>
            <p> Initializations</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">107</span>    <span class="k">def</span> <span class="nf">init</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-11'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-11'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">111</span>        <span class="bp">self</span><span class="o">.</span><span class="n">state_modules</span> <span class="o">=</span> <span class="p">[]</span>
<span class="lineno">112</span>
<span class="lineno">113</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">set_scalar</span><span class="p">(</span><span class="s2">&quot;loss.generator.*&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="lineno">114</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">set_scalar</span><span class="p">(</span><span class="s2">&quot;loss.discriminator.*&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="lineno">115</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">set_image</span><span class="p">(</span><span class="s2">&quot;generated&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="mi">1</span> <span class="o">/</span> <span class="mi">100</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-12'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-12'>#</a>
            </div>
            <p> <span ><span class="katex-display"><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.43056em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">∼</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">p</span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mclose">)</span></span></span></span></span></span></p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">117</span>    <span class="k">def</span> <span class="nf">sample_z</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-13'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-13'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">121</span>        <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-14'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-14'>#</a>
            </div>
            <p> Take a training step</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">123</span>    <span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">batch_idx</span><span class="p">:</span> <span class="n">BatchIndex</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-15'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-15'>#</a>
            </div>
            <p>Set model states </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">129</span>        <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">)</span>
<span class="lineno">130</span>        <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-16'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-16'>#</a>
            </div>
            <p>Get MNIST images </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">133</span>        <span class="n">data</span> <span class="o">=</span> <span class="n">batch</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-17'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-17'>#</a>
            </div>
            <p>Increment step in training mode </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">136</span>        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
<span class="lineno">137</span>            <span class="n">tracker</span><span class="o">.</span><span class="n">add_global_step</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-18'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-18'>#</a>
            </div>
            <p>Train the discriminator </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">140</span>        <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s2">&quot;discriminator&quot;</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-19'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-19'>#</a>
            </div>
            <p>Get discriminator loss </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">142</span>            <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_discriminator_loss</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-20'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-20'>#</a>
            </div>
            <p>Train </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">145</span>            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
<span class="lineno">146</span>                <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
<span class="lineno">147</span>                <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
<span class="lineno">148</span>                <span class="k">if</span> <span class="n">batch_idx</span><span class="o">.</span><span class="n">is_last</span><span class="p">:</span>
<span class="lineno">149</span>                    <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">&#39;discriminator&#39;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">)</span>
<span class="lineno">150</span>                <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-21'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-21'>#</a>
            </div>
            <p>Train the generator once in every <code  class="highlight"><span></span><span class="n">discriminator_k</span></code>
 </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">153</span>        <span class="k">if</span> <span class="n">batch_idx</span><span class="o">.</span><span class="n">is_interval</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">discriminator_k</span><span class="p">):</span>
<span class="lineno">154</span>            <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s2">&quot;generator&quot;</span><span class="p">):</span>
<span class="lineno">155</span>                <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_generator_loss</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-22'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-22'>#</a>
            </div>
            <p>Train </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">158</span>                <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="o">.</span><span class="n">is_train</span><span class="p">:</span>
<span class="lineno">159</span>                    <span class="bp">self</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
<span class="lineno">160</span>                    <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
<span class="lineno">161</span>                    <span class="k">if</span> <span class="n">batch_idx</span><span class="o">.</span><span class="n">is_last</span><span class="p">:</span>
<span class="lineno">162</span>                        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">&#39;generator&#39;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">)</span>
<span class="lineno">163</span>                    <span class="bp">self</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
<span class="lineno">164</span>
<span class="lineno">165</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">save</span><span class="p">()</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-23'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-23'>#</a>
            </div>
            <p> Calculate discriminator loss</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">167</span>    <span class="k">def</span> <span class="nf">calc_discriminator_loss</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-24'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-24'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">171</span>        <span class="n">latent</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sample_z</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="lineno">172</span>        <span class="n">logits_true</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="lineno">173</span>        <span class="n">logits_false</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">(</span><span class="n">latent</span><span class="p">)</span><span class="o">.</span><span class="n">detach</span><span class="p">())</span>
<span class="lineno">174</span>        <span class="n">loss_true</span><span class="p">,</span> <span class="n">loss_false</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator_loss</span><span class="p">(</span><span class="n">logits_true</span><span class="p">,</span> <span class="n">logits_false</span><span class="p">)</span>
<span class="lineno">175</span>        <span class="n">loss</span> <span class="o">=</span> <span class="n">loss_true</span> <span class="o">+</span> <span class="n">loss_false</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-25'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-25'>#</a>
            </div>
            <p>Log stuff </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">178</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">&quot;loss.discriminator.true.&quot;</span><span class="p">,</span> <span class="n">loss_true</span><span class="p">)</span>
<span class="lineno">179</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">&quot;loss.discriminator.false.&quot;</span><span class="p">,</span> <span class="n">loss_false</span><span class="p">)</span>
<span class="lineno">180</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">&quot;loss.discriminator.&quot;</span><span class="p">,</span> <span class="n">loss</span><span class="p">)</span>
<span class="lineno">181</span>
<span class="lineno">182</span>        <span class="k">return</span> <span class="n">loss</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-26'>
        <div class='docs doc-strings'>
            <div class='section-link'>
                <a href='#section-26'>#</a>
            </div>
            <p> Calculate generator loss</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">184</span>    <span class="k">def</span> <span class="nf">calc_generator_loss</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-27'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-27'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">188</span>        <span class="n">latent</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sample_z</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
<span class="lineno">189</span>        <span class="n">generated_images</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator</span><span class="p">(</span><span class="n">latent</span><span class="p">)</span>
<span class="lineno">190</span>        <span class="n">logits</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">discriminator</span><span class="p">(</span><span class="n">generated_images</span><span class="p">)</span>
<span class="lineno">191</span>        <span class="n">loss</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generator_loss</span><span class="p">(</span><span class="n">logits</span><span class="p">)</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-28'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-28'>#</a>
            </div>
            <p>Log stuff </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">194</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s1">&#39;generated&#39;</span><span class="p">,</span> <span class="n">generated_images</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">6</span><span class="p">])</span>
<span class="lineno">195</span>        <span class="n">tracker</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="s2">&quot;loss.generator.&quot;</span><span class="p">,</span> <span class="n">loss</span><span class="p">)</span>
<span class="lineno">196</span>
<span class="lineno">197</span>        <span class="k">return</span> <span class="n">loss</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-29'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-29'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">200</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">dataset_transforms</span><span class="p">)</span>
<span class="lineno">201</span><span class="k">def</span> <span class="nf">mnist_gan_transforms</span><span class="p">():</span>
<span class="lineno">202</span>    <span class="k">return</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
<span class="lineno">203</span>        <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
<span class="lineno">204</span>        <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">((</span><span class="mf">0.5</span><span class="p">,),</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,))</span>
<span class="lineno">205</span>    <span class="p">])</span>
<span class="lineno">206</span>
<span class="lineno">207</span>
<span class="lineno">208</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">discriminator_optimizer</span><span class="p">)</span>
<span class="lineno">209</span><span class="k">def</span> <span class="nf">_discriminator_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span>
<span class="lineno">210</span>    <span class="n">opt_conf</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span>
<span class="lineno">211</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">optimizer</span> <span class="o">=</span> <span class="s1">&#39;Adam&#39;</span>
<span class="lineno">212</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">discriminator</span><span class="o">.</span><span class="n">parameters</span><span class="p">()</span>
<span class="lineno">213</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">2.5e-4</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-30'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-30'>#</a>
            </div>
            <p>Setting exponent decay rate for first moment of gradient, <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqb" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.05278em">β</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:-0.05278em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> to <code  class="highlight"><span></span><span class="mf">0.5</span></code>
 is important. Default of <code  class="highlight"><span></span><span class="mf">0.9</span></code>
 fails. </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">217</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">betas</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">)</span>
<span class="lineno">218</span>    <span class="k">return</span> <span class="n">opt_conf</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-31'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-31'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">221</span><span class="nd">@option</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">generator_optimizer</span><span class="p">)</span>
<span class="lineno">222</span><span class="k">def</span> <span class="nf">_generator_optimizer</span><span class="p">(</span><span class="n">c</span><span class="p">:</span> <span class="n">Configs</span><span class="p">):</span>
<span class="lineno">223</span>    <span class="n">opt_conf</span> <span class="o">=</span> <span class="n">OptimizerConfigs</span><span class="p">()</span>
<span class="lineno">224</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">optimizer</span> <span class="o">=</span> <span class="s1">&#39;Adam&#39;</span>
<span class="lineno">225</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">generator</span><span class="o">.</span><span class="n">parameters</span><span class="p">()</span>
<span class="lineno">226</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">2.5e-4</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-32'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-32'>#</a>
            </div>
            <p>Setting exponent decay rate for first moment of gradient, <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord coloredeq eqb" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.05278em">β</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><span style="top:-2.5500000000000003em;margin-left:-0.05278em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mtight" style="">1</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> to <code  class="highlight"><span></span><span class="mf">0.5</span></code>
 is important. Default of <code  class="highlight"><span></span><span class="mf">0.9</span></code>
 fails. </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">230</span>    <span class="n">opt_conf</span><span class="o">.</span><span class="n">betas</span> <span class="o">=</span> <span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">)</span>
<span class="lineno">231</span>    <span class="k">return</span> <span class="n">opt_conf</span>
<span class="lineno">232</span>
<span class="lineno">233</span>
<span class="lineno">234</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">generator</span><span class="p">,</span> <span class="s1">&#39;mlp&#39;</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">Generator</span><span class="p">()</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">))</span>
<span class="lineno">235</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">discriminator</span><span class="p">,</span> <span class="s1">&#39;mlp&#39;</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">Discriminator</span><span class="p">()</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">))</span>
<span class="lineno">236</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">generator_loss</span><span class="p">,</span> <span class="s1">&#39;original&#39;</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">GeneratorLogitsLoss</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">label_smoothing</span><span class="p">)</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">))</span>
<span class="lineno">237</span><span class="n">calculate</span><span class="p">(</span><span class="n">Configs</span><span class="o">.</span><span class="n">discriminator_loss</span><span class="p">,</span> <span class="s1">&#39;original&#39;</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">c</span><span class="p">:</span> <span class="n">DiscriminatorLogitsLoss</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">label_smoothing</span><span class="p">)</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">c</span><span class="o">.</span><span class="n">device</span><span class="p">))</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-33'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-33'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">240</span><span class="k">def</span> <span class="nf">main</span><span class="p">():</span>
<span class="lineno">241</span>    <span class="n">conf</span> <span class="o">=</span> <span class="n">Configs</span><span class="p">()</span>
<span class="lineno">242</span>    <span class="n">experiment</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">&#39;mnist_gan&#39;</span><span class="p">,</span> <span class="n">comment</span><span class="o">=</span><span class="s1">&#39;test&#39;</span><span class="p">)</span>
<span class="lineno">243</span>    <span class="n">experiment</span><span class="o">.</span><span class="n">configs</span><span class="p">(</span><span class="n">conf</span><span class="p">,</span>
<span class="lineno">244</span>                       <span class="p">{</span><span class="s1">&#39;label_smoothing&#39;</span><span class="p">:</span> <span class="mf">0.01</span><span class="p">})</span>
<span class="lineno">245</span>    <span class="k">with</span> <span class="n">experiment</span><span class="o">.</span><span class="n">start</span><span class="p">():</span>
<span class="lineno">246</span>        <span class="n">conf</span><span class="o">.</span><span class="n">run</span><span class="p">()</span>
<span class="lineno">247</span>
<span class="lineno">248</span>
<span class="lineno">249</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>
<span class="lineno">250</span>    <span class="n">main</span><span class="p">()</span></pre></div>
        </div>
    </div>
    <div class='footer'>
        <a href="https://labml.ai">labml.ai</a>
    </div>
</div>
<script src=../../interactive.js?v=1"></script>
<script>
    function handleImages() {
        var images = document.querySelectorAll('p>img')

        for (var i = 0; i < images.length; ++i) {
            handleImage(images[i])
        }
    }

    function handleImage(img) {
        img.parentElement.style.textAlign = 'center'

        var modal = document.createElement('div')
        modal.id = 'modal'

        var modalContent = document.createElement('div')
        modal.appendChild(modalContent)

        var modalImage = document.createElement('img')
        modalContent.appendChild(modalImage)

        var span = document.createElement('span')
        span.classList.add('close')
        span.textContent = 'x'
        modal.appendChild(span)

        img.onclick = function () {
            console.log('clicked')
            document.body.appendChild(modal)
            modalImage.src = img.src
        }

        span.onclick = function () {
            document.body.removeChild(modal)
        }
    }

    handleImages()
</script>
</body>
</html>